Marktechpost

OCTOBER 6, 2024

The proposed MMTD-Set enhances traditional IFDL datasets by integrating text descriptions with visual tampering information. Don’t Forget to join our 50k+ ML SubReddit Interested in promoting your company, product, service, or event to over 1 Million AI developers and researchers? Let’s collaborate!

Large Language Models 116

Large Language Models Explainability Explainable AI AI 116

Unite.AI

MARCH 18, 2025

Certain large companies have control over a vast amount of data, which creates an uneven playing field wherein only a select few have access to information necessary to train AI models and drive innovation. Public web data should remain accessible to businesses, researchers, and developers. This is not how things should be.

AI Modeling 147

AI Modeling Automation Explainable AI AI Chatbots 147

AWS Machine Learning Blog

NOVEMBER 15, 2024

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

Responsible AI 113

Responsible AI Prompt Engineer Prompt Engineering AI 113

Unite.AI

MARCH 18, 2024

This content often fills the gap when data is scarce or diversifies the training material for AI models, sometimes without full recognition of its implications. While this expansion enriches the AI development landscape with varied datasets, it also introduces the risk of data contamination.

Data Integration 189

Data Integration AI AI Generative AI 189

Unite.AI

SEPTEMBER 13, 2023

Additionally, the continuously expanding datasets used by ML algorithms complicate explainability further. The larger the dataset, the more likely the system is to learn from both relevant and irrelevant information and spew “AI hallucinations” – falsehoods that deviate from external facts and contextual logic, however convincingly.

Explainability 278

Explainability Generative AI AI Tools Algorithm 278

Unite.AI

APRIL 9, 2024

As organizations strive for responsible and effective AI, Composite AI stands at the forefront, bridging the gap between complexity and clarity. The Need for Explainability The demand for Explainable AI arises from the opacity of AI systems, which creates a significant trust gap between users and these algorithms.

Composite AI 182

Composite AI Explainability Neural Network Black Box AI 182

IBM Journey to AI blog

FEBRUARY 28, 2024

IBM watsonx™ , an integrated AI, data and governance platform, embodies five fundamental pillars to help ensure trustworthy AI: fairness, privacy, explainability, transparency and robustness. This platform offers a seamless, efficient and responsible approach to AI development across various environments.

Generative AI 293

Generative AI Explainability AI AI 293

IBM Journey to AI blog

OCTOBER 16, 2023

It’s essential for an enterprise to work with responsible, transparent and explainable AI, which can be challenging to come by in these early days of the technology. But how trustworthy is that training data? They pointed out that the topic of training data, including its source and composition, is often overlooked.

Metadata 220

Metadata Explainability Automation Explainable AI 220

Unite.AI

JULY 2, 2024

Navigating this new, complex landscape is a legal obligation and a strategic necessity, and businesses using AI will have to reconcile their innovation ambitions with rigorous compliance requirements. GDPR's stringent data protection standards present several challenges for businesses using personal data in AI.

AI Strategy 162

AI Strategy Explainability AI AI 162

Viso.ai

FEBRUARY 12, 2024

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

Explainable AI 52

Explainable AI Explainability Deep Learning Neural Network 52

Towards AI

OCTOBER 19, 2024

Yet, for all their sophistication, they often can’t explain their choices — this lack of transparency isn’t just frustrating — it’s increasingly problematic as AI becomes more integrated into critical areas of our lives. What is Explainability AI (XAI)?

Explainability 105

Explainability Explainable AI Natural Language Processing Prompt Engineer 105

Dlabs.ai

AUGUST 16, 2022

This is the challenge that explainable AI solves. Explainable artificial intelligence shows how a model arrives at a conclusion. What is explainable AI? Explainable artificial intelligence (or XAI, for short) is a process that helps people understand an AI model’s output. Let’s begin.

Explainability 52

Explainability Explainable AI AI Modeling Artificial Intelligence 52

NVIDIA

MARCH 1, 2024

Trustworthy AI initiatives recognize the real-world effects that AI can have on people and society, and aim to channel that power responsibly for positive change. What Is Trustworthy AI? Trustworthy AI is an approach to AI development that prioritizes safety and transparency for those who interact with it.

AI 131

AI AI Algorithm Artificial Intelligence 131

Aiiot Talk

JULY 7, 2023

AI is today’s most advanced form of predictive maintenance, using algorithms to automate performance and sensor data analysis. This information serves as a baseline for comparison so the algorithm can identify unusual activity. IoT sensors that detect performance outside expected margins trigger the AI to alert maintenance personnel.

Black Box AI 130

Black Box AI Algorithm Explainability Explainable AI 130

Mlearning.ai

DECEMBER 31, 2023

Principles of Explainable AI( Source ) Imagine a world where artificial intelligence (AI) not only makes decisions but also explains them as clearly as a human expert. This isn’t a scene from a sci-fi movie; it’s the emerging reality of Explainable AI (XAI). What is Explainable AI?

Explainable AI 52

Explainable AI Explainability Neural Network Machine Learning 52

Unite.AI

JANUARY 12, 2024

Competitions also continue heating up between companies like Google, Meta, Anthropic and Cohere vying to push boundaries in responsible AI development. The Evolution of AI Research As capabilities have grown, research trends and priorities have also shifted, often corresponding with technological milestones.

Generative AI 189

Generative AI Neural Network ChatGPT Natural Language Processing 189

Towards AI

APRIL 2, 2024

On the other hand, new developments in techniques such as model merging (see story below from Sakana) can provide a new avenue for affordable development and improvement of open-source models. Hence, we are focused on making AI more accessible and releasing AI learning materials and courses! Why should you care?

LLM 103

LLM OpenAI Explainable AI AI 103

Marktechpost

DECEMBER 11, 2024

LG AI Research conducted extensive reviews to address potential legal risks like copyright infringement and personal information protection to ensure data compliance. Long-context benchmarks assessed the models capability to process and retrieve information from extended textual inputs, which is critical for RAG applications.

AI Researcher 87

AI Researcher AI Research Generative AI AI 87

Towards AI

OCTOBER 7, 2023

Last Updated on October 9, 2023 by Editorial Team Author(s): Lye Jia Jun Originally published on Towards AI. Balancing Ethics and Innovation: An Introduction to the Guiding Principles of Responsible AI Sarah, a seasoned AI developer, found herself at a moral crossroads. The other safeguards personal data but lacks speed.

Explainability 64

Explainability AI AI Algorithm 64

The MLOps Blog

FEBRUARY 27, 2025

For example, an LLM trained on predominantly European data might overrepresent those perspectives, unintentionally narrowing the scope of information or viewpoints it offers. Using aggregated data instead of raw personal information (e.g., How to integrate transparency, accountability, and explainability? Lets get into it!

LLM 64

LLM Large Language Models Explainability Machine Learning 64

ODSC - Open Data Science

FEBRUARY 18, 2025

AI Ethicists: As AI systems become more integrated into society, ethical considerations are paramount. AI ethicists specialize in ensuring that AI development and deployment align with ethical guidelines and regulatory standards, preventing unintended harm andbias.

Explainability 59

Explainability Automation AI AI 59

Viso.ai

JANUARY 21, 2025

Moreover, their ability to handle large datasets with fewer resources makes them a game-changer in AI development. ViTs vs. CNN (A Quick Comparison) Multimodal AI Integration Multimodal AI can process and integrate multiple types of data simultaneously such as text, images, video, and audio. Theyre becoming essential.

Computer Vision 52

Computer Vision Artificial Intelligence Artificial Intelligence Explainability 52

Pickl AI

JANUARY 29, 2024

As we navigate this landscape, the interconnected world of Data Science, Machine Learning, and AI defines the era of 2024, emphasising the importance of these fields in shaping the future. ’ As we navigate the expansive tech landscape of 2024, understanding the nuances between Data Science vs Machine Learning vs ai.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

NVIDIA

MARCH 18, 2025

This follows a wave of AI factory investments worldwide, as enterprises and countries accelerate AI-driven economic growth across every industry and region: India : Yotta Data Services has partnered with NVIDIA to launch the Shakti Cloud Platform , helping democratize access to advanced GPU resources.

AI 63

AI AI Data Platform Data Ingestion 63

ODSC - Open Data Science

OCTOBER 3, 2024

AI Development Lifecycle: Learnings of What Changed with LLMs Noé Achache | Engineering Manager & Generative AI Lead | Sicara Using LLMs to build models and pipelines has made it incredibly easy to build proof of concepts, but much more challenging to evaluate the models. An Intro to Federated Learning with Flower Daniel J.

Large Language Models 40

Large Language Models Machine Learning Data Scientist LLM 40

Pickl AI

APRIL 8, 2024

Privacy Concerns As AI systems become more sophisticated, they require access to vast amounts of data. This concerns about privacy and the potential for misuse of personal information. How Can We Ensure the Transparency of AI Systems?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm AI 52

Pickl AI

DECEMBER 10, 2024

Businesses face fines and reputational damage when AI decisions are deemed unethical or discriminatory. Socially, biased AI systems amplify inequalities, while data breaches erode trust in technology and institutions. Broader Ethical Implications Ethical AI development transcends individual failures.

Explainability 52

Explainability AI AI Artificial Intelligence 52

AI News

APRIL 25, 2024

He outlined a litany of potential pitfalls that must be carefully navigated—from AI hallucinations and emissions of falsehoods, to data privacy violations and intellectual property leaks from training on proprietary information. Pryon also emphasises explainable AI and verifiable attribution of knowledge sources.

Responsible AI 341

Responsible AI Big Data AI AI 341

AI Weekly

AUGUST 22, 2024

technologyreview.com Build your own AI-powered robot Hugging Face, the open-source AI powerhouse, has taken a significant step towards democratizing low-cost robotics with the release of a detailed tutorial that guides developers through the process of building and training their own AI-powered robots. pdf, Word, etc.)

Robotics 261

Robotics Artificial Intelligence Artificial Intelligence Large Language Models 261

IBM Journey to AI blog

SEPTEMBER 3, 2024

These systems inadvertently learn biases that might be present in the training data and exhibited in the machine learning (ML) algorithms and deep learning models that underpin AI development. Those learned biases might be perpetuated during the deployment of AI, resulting in skewed outcomes.

Explainability 215

Explainability Deep Learning AI AI 215

Flipboard

JUNE 20, 2023

Understanding AI’s mysterious “opaque box” is paramount to creating explainable AI. This can be simplified by considering that AI, like all other technology, has a supply chain. These are the mathematical formulas written to simulate functions of the brain, which underlie the AI programming.

AI Modeling 144

AI Modeling Explainability Algorithm Machine Learning 144

IBM Journey to AI blog

FEBRUARY 9, 2024

On a higher level, multimodal AI allows for a model to process more diverse data inputs, enriching and expanding the information available for training and inference. They make AI more explainable: the larger the model, the more difficult it is to pinpoint how and where it makes important decisions.

AI 298

AI AI Generative AI Artificial Intelligence 298